Plotly Express#
A high-level interface for creating visualizations with Plotly.
Simplifies the process of creating complex visualizations.
import plotly.express as px
fig = px.line([1, 2, 3, 4], [1, 4, 2, 3])
fig
fig = px.line(x=[1, 2, 3, 4], y=[1, 4, 2, 3])
dir(fig)
['__class__',
'__contains__',
'__delattr__',
'__dict__',
'__dir__',
'__doc__',
'__eq__',
'__format__',
'__ge__',
'__getattribute__',
'__getitem__',
'__getstate__',
'__gt__',
'__hash__',
'__init__',
'__init_subclass__',
'__iter__',
'__le__',
'__lt__',
'__module__',
'__ne__',
'__new__',
'__reduce__',
'__reduce_ex__',
'__repr__',
'__setattr__',
'__setitem__',
'__sizeof__',
'__str__',
'__subclasshook__',
'__weakref__',
'_add_annotation_like',
'_allow_disable_validation',
'_animation_duration_validator',
'_animation_easing_validator',
'_batch_layout_edits',
'_batch_trace_edits',
'_bracket_re',
'_build_dispatch_plan',
'_build_update_params_from_batch',
'_config',
'_data',
'_data_defaults',
'_data_objs',
'_data_validator',
'_dispatch_layout_change_callbacks',
'_dispatch_trace_change_callbacks',
'_filter_by_selector',
'_frame_objs',
'_frames_validator',
'_get_child_prop_defaults',
'_get_child_props',
'_get_subplot_coordinates',
'_get_subplot_rows_columns',
'_grid_ref',
'_grid_str',
'_has_subplots',
'_in_batch_mode',
'_index_is',
'_init_child_props',
'_initialize_layout_template',
'_ipython_display_',
'_is_dict_list',
'_is_key_path_compatible',
'_layout',
'_layout_defaults',
'_layout_obj',
'_layout_validator',
'_make_axis_spanning_layout_object',
'_normalize_trace_indexes',
'_perform_batch_animate',
'_perform_plotly_relayout',
'_perform_plotly_restyle',
'_perform_plotly_update',
'_perform_select_traces',
'_perform_update',
'_process_multiple_axis_spanning_shapes',
'_px_trendlines',
'_raise_invalid_rows_cols',
'_relayout_child',
'_repr_html_',
'_repr_mimebundle_',
'_restyle_child',
'_select_annotations_like',
'_select_layout_subplots_by_prefix',
'_select_subplot_coordinates',
'_selector_matches',
'_send_addTraces_msg',
'_send_animate_msg',
'_send_deleteTraces_msg',
'_send_moveTraces_msg',
'_send_relayout_msg',
'_send_restyle_msg',
'_send_update_msg',
'_set_in',
'_set_property',
'_set_trace_grid_position',
'_set_trace_uid',
'_str_to_dict_path',
'_subplot_not_empty',
'_to_ordered_dict',
'_valid_underscore_properties',
'_validate',
'_validate_get_grid_ref',
'_validate_rows_cols',
'add_annotation',
'add_bar',
'add_barpolar',
'add_box',
'add_candlestick',
'add_carpet',
'add_choropleth',
'add_choroplethmap',
'add_choroplethmapbox',
'add_cone',
'add_contour',
'add_contourcarpet',
'add_densitymap',
'add_densitymapbox',
'add_funnel',
'add_funnelarea',
'add_heatmap',
'add_histogram',
'add_histogram2d',
'add_histogram2dcontour',
'add_hline',
'add_hrect',
'add_icicle',
'add_image',
'add_indicator',
'add_isosurface',
'add_layout_image',
'add_mesh3d',
'add_ohlc',
'add_parcats',
'add_parcoords',
'add_pie',
'add_sankey',
'add_scatter',
'add_scatter3d',
'add_scattercarpet',
'add_scattergeo',
'add_scattergl',
'add_scattermap',
'add_scattermapbox',
'add_scatterpolar',
'add_scatterpolargl',
'add_scattersmith',
'add_scatterternary',
'add_selection',
'add_shape',
'add_splom',
'add_streamtube',
'add_sunburst',
'add_surface',
'add_table',
'add_trace',
'add_traces',
'add_treemap',
'add_violin',
'add_vline',
'add_volume',
'add_vrect',
'add_waterfall',
'append_trace',
'batch_animate',
'batch_update',
'data',
'for_each_annotation',
'for_each_coloraxis',
'for_each_geo',
'for_each_layout_image',
'for_each_legend',
'for_each_map',
'for_each_mapbox',
'for_each_polar',
'for_each_scene',
'for_each_selection',
'for_each_shape',
'for_each_smith',
'for_each_ternary',
'for_each_trace',
'for_each_xaxis',
'for_each_yaxis',
'frames',
'full_figure_for_development',
'get_subplot',
'layout',
'plotly_relayout',
'plotly_restyle',
'plotly_update',
'pop',
'print_grid',
'select_annotations',
'select_coloraxes',
'select_geos',
'select_layout_images',
'select_legends',
'select_mapboxes',
'select_maps',
'select_polars',
'select_scenes',
'select_selections',
'select_shapes',
'select_smiths',
'select_ternaries',
'select_traces',
'select_xaxes',
'select_yaxes',
'set_subplots',
'show',
'to_dict',
'to_html',
'to_image',
'to_json',
'to_ordered_dict',
'to_plotly_json',
'update',
'update_annotations',
'update_coloraxes',
'update_geos',
'update_layout',
'update_layout_images',
'update_legends',
'update_mapboxes',
'update_maps',
'update_polars',
'update_scenes',
'update_selections',
'update_shapes',
'update_smiths',
'update_ternaries',
'update_traces',
'update_xaxes',
'update_yaxes',
'write_html',
'write_image',
'write_json']
Explore the most common function types intended for users using the first word as the indicator
from collections import Counter
items = Counter([x.split("_")[0] for x in dir(fig) if x.split("_")[0]])
items
Counter({'add': 59,
'update': 18,
'for': 16,
'select': 16,
'to': 6,
'plotly': 3,
'write': 3,
'batch': 2,
'append': 1,
'data': 1,
'frames': 1,
'full': 1,
'get': 1,
'layout': 1,
'pop': 1,
'print': 1,
'set': 1,
'show': 1})
import pathlib
import pandas as pd
dir_data = pathlib.Path("data")
df = pd.read_csv(dir_data / "proteins" / "proteins.csv", index_col=0).T
df
| Reference | DMSO_rep1 | DMSO_rep2 | DMSO_rep3 | DMSO_rep4 | Suf_rep1 | Suf_rep2 | Suf_rep3 | Suf_rep4 |
|---|---|---|---|---|---|---|---|---|
| A5A613 | 27.180209 | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| P00350 | 28.151576 | 27.926204 | 27.653250 | 27.151643 | 27.441837 | 27.031610 | 27.814631 | 27.587217 |
| P00363 | 30.247131 | 30.261665 | 29.969625 | 29.470663 | 30.004725 | 30.085997 | 29.904057 | 29.575194 |
| P00370 | 27.459171 | 26.873349 | 26.599971 | 26.438623 | 27.399691 | 27.189188 | 27.139030 | 27.223715 |
| P00393 | 26.823758 | 26.756617 | 25.442346 | 25.798954 | 26.671118 | 26.885970 | 26.711192 | 26.320866 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Q57261 | 28.410859 | 27.940694 | 27.070328 | 26.679649 | 27.995432 | 27.055135 | 27.313219 | 26.643479 |
| Q59385-2 | 23.554913 | 25.240354 | NaN | 22.524292 | NaN | NaN | NaN | NaN |
| Q59385 | 27.640279 | 27.243650 | 27.525020 | 27.403753 | 27.498873 | 27.666957 | 27.708407 | 27.847610 |
| Q7DFV3 | 28.512794 | 27.620780 | 27.678892 | 27.255831 | 28.090220 | 27.525537 | 27.814369 | 27.605449 |
| Q93K97 | 27.223010 | 25.291110 | 24.358694 | 25.767196 | 25.956190 | 25.230565 | 26.103059 | 26.177716 |
2269 rows × 8 columns
x = df.iloc[:, 0]
px.histogram(x)
px.histogram(df)